For Journalists, Academics & Students · Health Care Technology
Health Care Technology Data for Journalists & Academics: 7 Ranked Sources
Health care technology data for journalists and academics comes from registries you can cite by name: ClinicalTrials.gov, MIMIC-IV and PhysioNet lead this ranking.
health care technology statistics for journalism · cited data sources for academic papers · where do journalists find data stories
API, files, or your warehouse. Daily, weekly, or hourly.
Which health care technology datasets should journalists cite first?
We rank for citability, not brand familiarity: relevance first (all seven of these records carry the maximum relevance rating), then Datadory's 10-point quality score inside each band. Every entry names its publisher, so an editor's or reviewer's first question - who published this, and when - already has an answer. The wider inventory behind this page sits in our health care technology data hub.
How do you check a clinical trial claim against the registered record?
The registry-first move is protocol matching. For device stories, work the same way upstream of the headline: EUDAMED's versioned, last-updated records show a device's regulatory standing in the EU system, and the Data.gov HHS Health Technology Catalog surfaces the underlying federal datasets with their own last-updated stamps.
Three habits make the check quotable. Name the publisher in the sentence, not a footnote. Record the date you queried, since 2 of these 7 sources change daily. And download the file rather than screenshotting a dashboard - 5 of the 7 ship CSV and 5 ship JSON, so the table behind your chart can travel with the story.
Which of these sources hold up in peer review?
Peer review turns on provenance, versioning and permission, and these records were selected for all three. MIMIC-IV ships versioned releases with a formal use agreement and a prescribed citation, the form reviewers expect for secondary analysis of intensive-care data. PhysioNet versions its curated datasets and pairs them with open software, letting a methods section point at an exact release.
The catalog context strengthens the pitch: the mean quality score across these 7 datasets is 8.86 against 7.81 across all 1,744 datasets Datadory catalogs, and catalog-wide 1,096 datasets (62.8%) score 8 or higher. This slice sits almost entirely above that bar - five of the seven score 9 or 10.
How fresh are these sources, and what should a citation include?
That spread is why a citation should always carry a query date. Catalog-wide, 22.6% of cataloged datasets.8% refresh at least weekly, so a daily-refreshing registry is the exception worth naming.
A working citation has four parts: publisher (NLM, ONC, the EU registry), exact dataset name as titled above, the format you pulled (5 of these 7 offer CSV; 5 offer JSON), and the access date. For MIMIC-IV, substitute the version number and the use-agreement citation the repository prescribes.
Straight answers
Where do health care technology statistics for journalism come from?
From registries and federal portals rather than vendor reports. ClinicalTrials.gov verifies what a trial was registered to test, EUDAMED confirms a device's EU regulatory standing, and the ONC Health IT Dashboard publishes public-domain data briefs with the raw datasets behind them.
Which health care technology data sources can be cited in an academic paper?
Five of these 7 datasets score 9 or 10 on Datadory's quality scale, and the slice averages 8.86 against a 7.81 catalog-wide mean.
Where do journalists find data stories in health care technology?
Start where registration meets reality: compare a trial's press coverage against its ClinicalTrials.gov protocol. Then check devices against EUDAMED's versioned EU records and health-IT adoption against ONC's quarterly dashboards.
Rows before rollout
Sample rows from any shelf entry — the field dictionary and coverage notes ride along. If the shelf misses what you need, say so; sourcing requests are half our job.
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